Recovering intrinsic images from natural photos is one of the foundational problems in computer vision. This mission always falls into an ill-posed problem. In order to attain reasonable estimations, one strategy is to use multiple images of the scene under various lightings so as to narrow the solution space, whereas another is to utilize priori knowledge as constraints. In this paper, we present an approach to deriving intrinsic images (including illumination images and reflectance images) that employs both strategies. Specifically, the Total Variation (TV) constraint is imposed because of its excellent edge preservation ability and simple parameter settings. To solve this objective function efficiently, we propose using the Alternating Direction Method of Multipliers (AD-MM) to build an iterative numerical scheme. Experimental results illustrate the effectiveness of the proposed model and the numerical scheme.

Recovering Intrinsic Images by Minimizing Image Complexity

STEFANI, NICOLA;FUSIELLO, Andrea
2015-01-01

Abstract

Recovering intrinsic images from natural photos is one of the foundational problems in computer vision. This mission always falls into an ill-posed problem. In order to attain reasonable estimations, one strategy is to use multiple images of the scene under various lightings so as to narrow the solution space, whereas another is to utilize priori knowledge as constraints. In this paper, we present an approach to deriving intrinsic images (including illumination images and reflectance images) that employs both strategies. Specifically, the Total Variation (TV) constraint is imposed because of its excellent edge preservation ability and simple parameter settings. To solve this objective function efficiently, we propose using the Alternating Direction Method of Multipliers (AD-MM) to build an iterative numerical scheme. Experimental results illustrate the effectiveness of the proposed model and the numerical scheme.
2015
978-3-905674-97-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1070203
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact